get_MIE_file

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must carry the full burden. It describes a read-like operation (getting a file) and emphasizes it as a prerequisite for queries, but does not disclose details like idempotency, error handling, or any side effects. The instruction provides some behavioral context, but more transparency would be helpful (e.g., 'This tool returns a file and has no side effects.').

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, with the critical usage instruction in bold and front-loaded. The two sentences cover purpose and usage without waste. However, it could be slightly more structured by separating the usage instruction from the definition. Still, it is efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description tells the agent to call this tool before SPARQL queries and explains what the MIE file contains. However, it does not explain how to interpret the file or what to do with it next. Additionally, the parameters dbname and db are left undocumented, which reduces completeness. Given the output schema exists, the return is somewhat covered, but the tool's role in the workflow could be elaborated.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has three parameters: database (with description), dbname, and db (both without description, 33% coverage). The tool description does not explain the purpose of dbname or db or how they relate to database. The user is left guessing which to use. The description should clarify these parameters to compensate for the sparse schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves the MIE file containing schema and examples for a database. It also provides a strong usage instruction: 'At the start of any task, identify ALL databases needed and call this tool for EACH of them before writing any SPARQL queries.' This differentiates it from query tools like run_sparql and database-listing tools like find_databases.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly tells the agent when to use the tool: at the start of a task, for each needed database, and before any SPARQL queries. It also states when not to use it: 'Do not query a database until its MIE file has been read.' This provides clear contextual guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.